Role of prediabetes in stroke

Mijajlović, Milija; Aleksić, Vuk; Šternić, Nadežda; Mirkovic, Mihailo; Bornstein, Natan M.

doi:10.2147/ndt.s128807

Cited by 29 publications

(20 citation statements)

References 52 publications

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“…In our study, we observed that 38.7% of intracerebral hemorrhage patients were defined as PreDM at admission, which is consistent with the occurrence rate of PreDM among ischemic stroke patients and the general population (Mijajlovic, Aleksic, Sternic, Mirkovic, & Bornstein, ; Vijayakumar et al, ). We found that the PreDM group had a higher risk of poor functional outcome than the non‐DM group among intracerebral hemorrhage patients.…”

Section: Discussionsupporting

confidence: 88%

Prediabetes is associated with poor functional outcome in patients with intracerebral hemorrhage

et al. 2020

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Introduction:The association between prediabetes and functional outcome in cerebrovascular diseases is controversial. No study has explored the relationship between prediabetes and functional outcome in intracerebral hemorrhage patients.Our study aimed to explore the association between prediabetes and functional outcome in intracerebral hemorrhage patients 1 month poststroke. Methods:One hundred and fifty intracerebral hemorrhage patients were consecutively recruited within the first 24 hr after admission and were followed up for 1 month. Patients were divided into a diabetes mellitus group, a prediabetes group, and a nondiabetic group by fasting glucose levels, 2-hr postprandial blood glucose levels, and glycosylated hemoglobin levels. Patients with modified Rankin Scale scores >2 at 1 month were defined as having a poor functional outcome. Results:The prediabetes group had a higher risk of poor functional outcome than the nondiabetic group in intracerebral hemorrhage patients (37.9% vs. 9.8%, χ 2 = 11.521, p = .001). According to the logistic regression analyses, prediabetes was associated with a poor functional outcome in intracerebral hemorrhage patients after adjusting for confounding factors (odds ratio = 6.167, 95% confidence interval = 1.403-27.102, p = .016). Conclusions:Our findings show that prediabetes is associated with a poor functional outcome in intracerebral hemorrhage patients 1 month poststroke. K E Y W O R D S diabetes mellitus, functional outcome, intracerebral hemorrhage, prediabetes How to cite this article: Wang Q, Huang G, Chen F, et al. Prediabetes is associated with poor functional outcome in patients with intracerebral hemorrhage. Brain Behav.

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Section: Discussionsupporting

confidence: 88%

Prediabetes is associated with poor functional outcome in patients with intracerebral hemorrhage

et al. 2020

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“…The estimated prevalence of Chinese adults with prediabetes was 50.1%, and 493.4 million may have had prediabetes in 2010 [ 2 ]. Prediabetes is an important risk factor for diabetes [ 3 ] and many other diseases, such as cardiovascular diseases (CVD) [ 4 ], stroke [ 5 ], and nephropathy [ 6 ]. It was reported that the annual risk of progressing to diabetes in people with prediabetes was 5%–10% and up to 70% prediabetic patients would develop diabetes after years [ 7 ].…”

Section: Introductionmentioning

confidence: 99%

Association between the Hypertriglyceridemic Waist Phenotype and Prediabetes in Chinese Adults Aged 40 Years and Older

Zhao

Yang

Wang

et al. 2018

Journal of Diabetes Research

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Objective To investigate the association between the hypertriglyceridemic waist (HTGW) phenotype and prediabetes in Chinese adults aged 40 years and older. Methods 12757 adults (4101 men and 8656 women) without diabetes or cardiovascular and cerebrovascular diseases, free of using lipid-modified agents, were enrolled in this cross-sectional study. The HTGW phenotype was defined as elevated serum triglyceride concentrations and enlarged waist circumference. A two-hour post 75 g oral glucose tolerance test was performed in all participants. Multiple logistic regression analysis was used to evaluate the relationship of the HTGW phenotype with prediabetes. Results Individuals with the HTGW phenotype had a higher adjusted odds ratio (OR: 1.70; 95% CI: 1.48–1.95) of prediabetes than those without the phenotype. There existed a strong relationship of the HTGW phenotype with impaired glucose tolerance (IGT) (OR: 1.83; 95% CI: 1.57–2.13), but not with impaired fasting glucose (IFG) (OR: 0.87; 95% CI: 0.65–1.17). Only women with the HTGW phenotype are significantly associated with the combined IFG and IGT (OR: 1.83; 95% CI: 1.28–2.62). Conclusions The HTGW phenotype was a useful risk indicator and a practical screening tool to benefit in the early diagnosis and intervention for prediabetes, particularly for IGT and the combined IFG and IGT.

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“…Stroke is one of the main causes of death and disability worldwide [ 1 ]. Due to lack of effective treatment, it is difficult to cure stroke patients completely.…”

Section: Introductionmentioning

confidence: 99%

The Probability of Ischaemic Stroke Prediction with a Multi-Neural-Network Model

Liu

Yin

Yang

2020

Sensors

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As is known, cerebral stroke has become one of the main diseases endangering people’s health; ischaemic strokes accounts for approximately 85% of cerebral strokes. According to research, early prediction and prevention can effectively reduce the incidence rate of the disease. However, it is difficult to predict the ischaemic stroke because the data related to the disease are multi-modal. To achieve high accuracy of prediction and combine the stroke risk predictors obtained by previous researchers, a method for predicting the probability of stroke occurrence based on a multi-model fusion convolutional neural network structure is proposed. In such a way, the accuracy of ischaemic stroke prediction is improved by processing multi-modal data through multiple end-to-end neural networks. In this method, the feature extraction of structured data (age, gender, history of hypertension, etc.) and streaming data (heart rate, blood pressure, etc.) based on a convolutional neural network is first realized. A neural network model for feature fusion is then constructed to realize the feature fusion of structured data and streaming data. Finally, a predictive model for predicting the probability of stroke is obtained by training. As shown in the experimental results, the accuracy of ischaemic stroke prediction reached 98.53%. Such a high prediction accuracy will be helpful for preventing the occurrence of stroke.

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Role of prediabetes in stroke

Cited by 29 publications

References 52 publications

Prediabetes is associated with poor functional outcome in patients with intracerebral hemorrhage

Prediabetes is associated with poor functional outcome in patients with intracerebral hemorrhage

Association between the Hypertriglyceridemic Waist Phenotype and Prediabetes in Chinese Adults Aged 40 Years and Older

The Probability of Ischaemic Stroke Prediction with a Multi-Neural-Network Model

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